Varicella Zoster–Specific CD4+Foxp3+ T Cells Accumulate after Cutaneous Antigen Challenge in Humans
Bibliographic record
Abstract
We investigated the relationship between varicella zoster virus (VZV)-specific memory CD4(+) T cells and CD4(+)Foxp3(+) regulatory T cells (Tregs) that accumulate after intradermal challenge with a VZV skin test Ag. VZV-specific CD4(+) T cells were identified with a MHC class II tetramer or by intracellular staining for either IFN-γ or IL-2 after Ag rechallenge in vitro. VZV-specific T cells, mainly of a central memory (CD45RA(-)CD27(+)) phenotype, accumulate at the site of skin challenge compared with the blood of the same individuals. This resulted in part from local proliferation because >50% of tetramer defined Ag-specific CD4(+) T cells in the skin expressed the cell cycle marker Ki67. CD4(+)Foxp3(+) T cells had the characteristic phenotype of Tregs, namely CD25(hi)CD127(lo)CD39(hi) in both unchallenged and VZV challenged skin and did not secrete IFN-γ or IL-2 after antigenic restimulation. The CD4(+)Foxp3(+) T cells from unchallenged skin had suppressive activity, because their removal led to an increase in cytokine secretion after activation. After VZV Ag injection, Foxp3(+)CD25(hi)CD127(lo)CD39(hi) T cells were also found within the VZV tetramer population. Their suppressive activity could not be directly assessed by CD25 depletion because activated T cells in the skin were also CD25(+). Nevertheless, there was an inverse correlation between decreased VZV skin responses and proportion of CD4(+)Foxp3(+) T cells present, indicating indirectly their inhibitory activity in vivo. These results suggest a linkage between the expansion of Ag-specific CD4(+) T cells and CD4(+) Tregs that may provide controlled responsiveness during Ag-specific stimulation in tissues.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".